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NTT Research Joins MIT AI Hardware Program

Becomes Inaugural Industrial Member in Group Coordinating MIT AI Research

NTT Research, Inc., a subsidiary of NTT announced that it has joined the Massachusetts Institute of Technology (MIT) Artificial Intelligence (AI) Hardware Program as an inaugural industrial member. A leading academic center for AI research, MIT has established this program to coordinate various research groups at MIT that are related to this topic. A key strategic initiative of the program is to apply hardware technologies to improve AI engines from the perspective of its performance and energy consumption. NTT Research has joined for a three-year term that began in January 2022.

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@NTTResearch has become an inaugural member of the MIT AI Hardware Program alongside @Amazon, @ADI_News, @ASMLcompany and @TWSemicon. @MITEngineering @MIT_SCC #UpgradeReality #TechForGood

“Expanding our relationship with MIT through this new program makes good sense, as it builds upon our existing and productive engagements, which have generated two dozen papers and several patents in less than three years, and makes available additional access to MIT’s extensive research activities in AI, providing further opportunities for collaboration,” said Kazuhiro Gomi, President & CEO of NTT Research, Inc.

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For NTT Research, membership in the MIT AI Hardware Program will encompass the PHI Lab’s existing research and two additional topics. The program will address areas that support novel technologies and architectures, including complementary metal-oxide-semiconductor (CMOS) roadmaps, monolithic 3D systems, analog non-volatile memory devices, and previously undetected or reported concepts. It will also include areas of particular interest, such as “edge” applications and integrated intelligent sensors. Driving research in these areas of AI is growing concern about scalability and energy consumption. While the software and service sectors of the AI industry capture attention in the public, in part because of their tremendous growth rates, hardware constraints are emerging as a gating issue. The computational requirements for the machine learning subset of AI, for instance, are accelerating rapidly, especially where neural networks are concerned. Such a surge in computational requirements also has an impact on environmental sustainability, as the energy consumption grows rapidly to support such computational power. To address these issues, promising solutions will require attending to hardware, and perhaps revolutionizing components and architectures.

NTT Research has entered a similar industrial partnership with the Simons Institute for the Theory of Computing; however, most external collaborations take the form of JRAs. In addition to MIT, nine other universities have agreed to conduct joint research with the NTT Research PHI Lab. These include the California Institute of Technology (CalTech), Cornell, Harvard University, Notre Dame University, Stanford University, Swinburne University of Technology, the Tokyo Institute of Technology, the University of Michigan, and the University of Tokyo. The NASA Ames Research Center in Silicon Valley and 1QBit, a private quantum computing software company, have also entered joint research agreements with the PHI Lab.

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